Question

 

1) Give 2 examples of studies that can use a t-test for independent samples in your area of study or interest.

2) Give 2 examples of studies that can use a t-test for dependent samples in your area of study or interest.

3) What are TWO interesting insights you know about hypothesis testing?

Answer 1

Solution)

Part(1)

Independent Sample t –test examples

Independent sample t-test is a statistical technique that is used to analyze the mean comparison of two independent groups.,

Example 1:

Suppose we want to know whether the salary of male faculty members in private institution is equal to salary of female faculty members.

Researcher collected data from 20 male and 20 female faculty members in private institution to know the difference.

Our hypothesis in this case are:

H0= there is not significant difference in Male and Female Salaries.

H1= there is significant difference in Male and Female Salaries.

Example 2:

As an example, we have a population of 20 people selected randomly (10 women and 10 men). We want to know whether women’s average weight is significantly different from men’s average weight.

In this typical example the two samples being compared are completely unrelated and you have to use independent samples t test.

In this case our Hypothesis are:

H0= there is not significant difference in weight of male and female.

H1= there is significant difference in weight of male and female.

Part(2)

Dependent Samples t –test OR Paired t-test   examples.

The paired sample t-test, sometimes called the dependent sample t-test

In a paired sample t-test, each subject or entity is measured twice, resulting in Pairs of observations like ( before and After).

Example 1:

Suppose you are interested in evaluating the effectiveness of a company training program. One approach you might consider would be to measure the performance of a sample of employees before and after completing the program, and analyze the differences using a paired sample t-test

In this case our Hypothesis are:

H0=there is not significant effect of training programme on performance of employees.

H1=there is significant effect of training programme on performance of employees.

Example 2:

ABC University arranges a Special Faculty Development Programme for one segment of its teachers

The university wants to measure the change in the attitude of its Teachers after the Faculty Development programme(FDP)

For this purpose it has used a well designed questionnaire which consist of 10 questions on a 1 to 5 rating scale ( 1 is strongly disagree)’ and (5 is strongly agree)

The university selected a random sample of 20 teachers and measure their response before FDP and After FDP.

In this case our hypothesis are

H0 = there is not Significant effect of FDP on teachers attitude.

        i.e average response  before Fdp is equal to after fdp.

H1 = there is significant effect of FDP on teachers attitude.

i.e average response  before fdp is not equal to after fdp.

Part(3)

Hypothesis testing is used to take inference after conducting a experiment .

setting up of null hypothesis H0 and alternative hypothesis H1 in terms of range of the parameter values.

the choice of suitable statistic t called the test statistic.

we write our null hypothesis(H0) always as

H0= there is not significant difference or there is no difference. between two groups

and we write our alternatice Hypothesis(H1) as

H1= there is significant difference or there is difference between two groups.

we reject the null hypothesis(H0)  if test statistic calculated value is greater than tabulated value

or reject the null hypothesis(H0) if p-value<0.05 or any given level of significance.

we Do not reject the null hypothesis(H0) if test statistic calculated value is less than tabulated value.

or Do not reject the null hypothesis(H0) if p-value>0.05 or any given level of significance.